B d@sVdZddlZddlmZmZddZddZdd d Zdd d Zdd dZ ddZ dS)z8 Functions for removing frequency lines from real data. N) TimeSerieszeroscCs4tdd|D}tdd|D}|d|S)a Get the median value of a list of complex numbers. Parameters ---------- complex_list: list List of complex numbers to calculate the median. Returns ------- a + 1.j*b: complex number The median of the real and imaginary parts. cSsg|] }|jqS)real).0complex_numberrr_/work/yifan.wang/ringdown/master-ringdown-env/lib/python3.7/site-packages/pycbc/strain/lines.py #sz"complex_median..cSsg|] }|jqSr)imag)rrrrrr %sy?)numpyZmedian)Z complex_listZ median_realZ median_imagrrrcomplex_medians    r c Cs|j|jkst|j|jks tt||j}g}xztt|j|D]d}|||d|}}t|||}dt|j||jt |j|||} | | qFWt |} |t | t | fS)a Calculate the time-domain inner product averaged over bins. Parameters ---------- data1: pycbc.types.TimeSeries First data set. data2: pycbc.types.TimeSeries Second data set, with same duration and sample rate as data1. bin_size: float Duration of the bins the data will be divided into to calculate the inner product. Returns ------- inner_prod: list The (complex) inner product of data1 and data2 obtained in each bin. amp: float The absolute value of the median of the inner product. phi: float The angle of the median of the inner product. )durationAssertionError sample_rateintrangelensumdatarr conjugateappendr absZangle) Zdata1Zdata2bin_sizeseglenZ inner_prodidxstartendZnormZbin_prodZ inner_medianrrravg_inner_product)s0rr cCsVttt||j|jd}|jt|}dtj|||}|t d||_ |S)a  Simple time-domain model for a frequency line. Parameters ---------- freq: float Frequency of the line. data: pycbc.types.TimeSeries Reference data, to get delta_t, start_time, duration and sample_times. tref: float Reference time for the line model. amp: {1., float}, optional Amplitude of the frequency line. phi: {0. float}, optional Phase of the frequency line (radians). Returns ------- freq_line: pycbc.types.TimeSeries A timeseries of the line model with frequency 'freq'. The returned data are complex to allow measuring the amplitude and phase of the corresponding frequency line in the strain data. For extraction, use only the real part of the data. )delta_tepochry?) rrrr start_timeZ sample_timesfloatr piexpr)freqrtrefampphiZ freq_linetimesalpharrr line_modelOs  r,cCs4t|||d}t|||d\}}}t|||||dS)a] Find the parameter of the line with frequency 'freq' in the data. Parameters ---------- freq: float Frequency of the line to find in the data. data: pycbc.types.TimeSeries Data from which the line wants to be measured. tref: float Reference time for the frequency line. bin_size: {1, float}, optional Duration of the bins the data will be divided into for averaging. Returns ------- line_model: pycbc.types.TimeSeries A timeseries containing the frequency line with the amplitude and phase measured from the data. )r')r)r'r(r))r,r)r&rr'rZ template_line_r(r)rrr matching_linepsr.cCsB|dkrt|j}x*|D]"}t||||jd}||jj8}qW|S)a Extract the calibration lines from strain data. Parameters ---------- freqs: list List containing the frequencies of the calibration lines. data: pycbc.types.TimeSeries Strain data to extract the calibration lines from. tref: {None, float}, optional Reference time for the line. If None, will use data.start_time. Returns ------- data: pycbc.types.TimeSeries The strain data with the calibration lines removed. N)r)r#r"r.rrr)freqsrr'r&Z measured_linerrrcalibration_liness   r0c Cs||krtd||jkr"tdtdt|j|dd}||j}t|j}x0|D]&}x|D]}t||t|d|} } t||| | ||d} t t | } t t t | | j | jd} |dkr| jt | dd | t | dd 9<nL||d krF| jd t | d| d t | d9<n| j| 9_| j| j9_|j| | | jj8<qhWqZW|S) a' Extract time-varying (wandering) lines from strain data. Parameters ---------- freqs: list List containing the frequencies of the wandering lines. data: pycbc.types.TimeSeries Strain data to extract the wandering lines from. chunk: float Duration of the chunks the data will be divided into to account for the time variation of the wandering lines. Should be smaller than data.duration, and allow for at least a few chunks. avg_bin: float Duration of the bins each chunk will be divided into for averaging the inner product when measuring the parameters of the line. Should be smaller than chunk. Returns ------- data: pycbc.types.TimeSeries The strain data with the wandering lines removed. zNThe bin size for averaging the inner product must be less than the chunk size.z3The chunk size must be less than the data duration.rg?r )r)r r!rN) ValueErrorrr Zarangerrr#r"r.ZhanningrrZonesr rr)r/rchunkZavg_binZstepsrr'r&steprrZ chunk_lineZ hann_windowZ apply_hannrrr clean_datas4      "r5)r r)r )N) __doc__r Z pycbc.typesrrr rr,r.r0r5rrrrs& !